docs: clarify difference between load and open in docstrings

[SAY-5]

Closes #463. Adds Notes and See Also cross-references to the load and open docstrings explaining that load eagerly reads data into in-memory NumPy arrays while open returns a lazy Array/Group backed by the store, addressing the maintainer's note that "the documentation could definitely be improved here, PR welcome."

TODO:

• Add unit tests and/or doctests in docstrings
• Add docstrings and API docs for any new/modified user-facing classes and functions
• New/modified features documented in docs/user-guide/*.md
• Changes documented as a new file in changes/
• GitHub Actions have all passed
• Test coverage is 100% (Codecov passes)

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 93.50%. Comparing base (e29ddd2) to head (e0fa87d).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #3984   +/-   ##
=======================================
  Coverage   93.50%   93.50%           
=======================================
  Files          90       90           
  Lines       11981    11981           
=======================================
  Hits        11203    11203           
  Misses        778      778           

Files with missing lines	Coverage Δ
src/zarr/api/asynchronous.py	94.05% <ø> (ø)
src/zarr/api/synchronous.py	92.95% <ø> (ø)

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[maxrjones]

Thanks for this PR, and sorry for the slow review!

I left some comments since the loaded array type is not always NumPy.

[maxrjones]

Suggested change

	`load` eagerly reads data into an in-memory NumPy array, while `open` returns a
	`load` eagerly reads data into an in-memory array, while `open` returns a

[maxrjones]

Suggested change

	instead when you want the data eagerly read into an in-memory NumPy array.
	instead when you want the data eagerly read into an in-memory array
	(a NumPy array by default).

[maxrjones]

Suggested change

	instead when you want the data eagerly read into an in-memory NumPy array.
	instead when you want the data eagerly read into an in-memory array (a
	NumPy array by default).

[maxrjones]

Suggested change

	returns it as an in-memory NumPy array (or a dict of NumPy arrays for a group).
	returns it as an in-memory array (or a dict of arrays for a group).
	The array type is NumPy by default, but follows the configured
	buffer prototype (for example, CuPy for GPU use cases).

[maxrjones]

Suggested change

	returns it as an in-memory NumPy array (or a dict of NumPy arrays for a group).
	returns it as an in-memory array (or a dict of arrays for a group).
	The array type is NumPy by default, but follows the configured
	buffer prototype (for example, CuPy for GPU use cases).